Mining significant association rules from educational data using critical relative support approach
Least association rules are the association rules that consist of the least item. These rules are very important and critical since they can be used to detect the infrequent events and exceptional cases. However, the formulation of measurement to efficiently discover least association rules is quite...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier Ltd.
2011
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| Online Access: | http://umpir.ump.edu.my/id/eprint/24805/ http://umpir.ump.edu.my/id/eprint/24805/1/Mining%20significant%20association%20rules%20from%20educational%20data%20using%20critical%20relative%20support%20approach.pdf |
| _version_ | 1848822127357067264 |
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| author | Zailani, Abdullah Herawan, Tutut Noraziah, Ahmad Mustafa, Mat Deris |
| author_facet | Zailani, Abdullah Herawan, Tutut Noraziah, Ahmad Mustafa, Mat Deris |
| author_sort | Zailani, Abdullah |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | Least association rules are the association rules that consist of the least item. These rules are very important and critical since they can be used to detect the infrequent events and exceptional cases. However, the formulation of measurement to efficiently discover least association rules is quite intricate and not really straight forward. In educational domain, this information is very useful since it can be used as a base for investigating and enhancing the current educational standards and managements. Therefore, this paper proposes a new measurement called Critical Relative Support (CRS) to mine critical least association rules from educational context. Experiment with students’ examination result dataset shows that this approach can be used to reveal the significant rules and also can reduce up to 98% of uninterested association rules. |
| first_indexed | 2025-11-15T02:36:18Z |
| format | Article |
| id | ump-24805 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T02:36:18Z |
| publishDate | 2011 |
| publisher | Elsevier Ltd. |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-248052019-07-08T06:27:09Z http://umpir.ump.edu.my/id/eprint/24805/ Mining significant association rules from educational data using critical relative support approach Zailani, Abdullah Herawan, Tutut Noraziah, Ahmad Mustafa, Mat Deris QA76 Computer software Least association rules are the association rules that consist of the least item. These rules are very important and critical since they can be used to detect the infrequent events and exceptional cases. However, the formulation of measurement to efficiently discover least association rules is quite intricate and not really straight forward. In educational domain, this information is very useful since it can be used as a base for investigating and enhancing the current educational standards and managements. Therefore, this paper proposes a new measurement called Critical Relative Support (CRS) to mine critical least association rules from educational context. Experiment with students’ examination result dataset shows that this approach can be used to reveal the significant rules and also can reduce up to 98% of uninterested association rules. Elsevier Ltd. 2011 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/24805/1/Mining%20significant%20association%20rules%20from%20educational%20data%20using%20critical%20relative%20support%20approach.pdf Zailani, Abdullah and Herawan, Tutut and Noraziah, Ahmad and Mustafa, Mat Deris (2011) Mining significant association rules from educational data using critical relative support approach. Procedia - Social and Behavioral Sciences, 28. pp. 97-101. ISSN 1877-0428, ESSN: 1877-0428. (Published) https://doi.org/10.1016/j.sbspro.2011.11.020 https://doi.org/10.1016/j.sbspro.2011.11.020 |
| spellingShingle | QA76 Computer software Zailani, Abdullah Herawan, Tutut Noraziah, Ahmad Mustafa, Mat Deris Mining significant association rules from educational data using critical relative support approach |
| title | Mining significant association rules from educational data using critical relative support approach |
| title_full | Mining significant association rules from educational data using critical relative support approach |
| title_fullStr | Mining significant association rules from educational data using critical relative support approach |
| title_full_unstemmed | Mining significant association rules from educational data using critical relative support approach |
| title_short | Mining significant association rules from educational data using critical relative support approach |
| title_sort | mining significant association rules from educational data using critical relative support approach |
| topic | QA76 Computer software |
| url | http://umpir.ump.edu.my/id/eprint/24805/ http://umpir.ump.edu.my/id/eprint/24805/ http://umpir.ump.edu.my/id/eprint/24805/ http://umpir.ump.edu.my/id/eprint/24805/1/Mining%20significant%20association%20rules%20from%20educational%20data%20using%20critical%20relative%20support%20approach.pdf |